Monthly Archives: October 2018

Evidence-based policymaking and the ‘new policy sciences’

image policy process round 2 25.10.18

[I wasn’t happy with the first version, so this is version 2, to be enjoyed with the ppt MP3 ]

In the ‘new policy sciences’, Chris Weible and I advocate:

  • a return to Lasswell’s vision of combining policy analysis (to recommend policy change) and policy theory (to explain policy change), but
  • focusing on a far larger collection of actors (beyond a small group at the centre),
  • recognising new developments in studies of the psychology of policymaker choice, and
  • building into policy analysis the recognition that any policy solution is introduced in a complex policymaking environment over which no-one has control.

However, there is a lot of policy theory out there, and we can’t put policy theory together like Lego to produce consistent insights to inform policy analysis.

Rather, each concept in my image of the policy process represents its own literature: see these short explainers on the psychology of policymaking, actors spread across multi-level governance, institutions, networks, ideas, and socioeconomic factors/ events.

What the explainers don’t really project is the sense of debate within the literature about how best to conceptualise each concept. You can pick up their meaning in a few minutes but would need a few years to appreciate the detail and often-fundamental debate.

Ideally, we would put all of the concepts together to help explain policymaker choice within a complex policymaking environment (how else could I put up the image and present is as one source of accumulated wisdom from policy studies?). Peter John describes such accounts as ‘synthetic’. I have also co-authored work with Tanya Heikkila – in 2014 and 2017 to compare the different ways in which ‘synthetic’ theories conceptualise the policy process.

However, note the difficulty of putting together a large collection of separate and diverse literatures into one simple model (e.g. while doing a PhD).

On that basis, I’d encourage you to think of these attempts to synthesise as stories. I tell these stories a lot, but someone else could describe theory very differently (perhaps by relying on fewer male authors or US-derived theories in which there is a very specific reference points and positivism is represented well).

The example of EBPM

I have given a series of talks to explain why we should think of ‘evidence-based policymaking’ as a myth or political slogan, not an ideal scenario or something to expect from policymaking in the real world. They usually involve encouraging framing and storytelling rather than expecting evidence to speak for itself, and rejecting the value of simple models like the policy cycle. I then put up an image of my own and encourage people to think about the implications of each concept:

SLIDE simple advice from hexagon image policy process 24.10.18

I describe the advice as simple-sounding and feasible at first glance, but actually a series of Herculean* tasks:

  • There are many policymakers and influencers spread across government, so find out where the action is, or the key venues in which people are making authoritative decisions.
  • Each venue has its own ‘institutions’ – the formal and written, or informal and unwritten rules of policymaking – so learn the rules of each venue in which you engage.
  • Each venue is guided by a fundamental set of ideas – as paradigms, core beliefs, monopolies of understanding – so learn that language.
  • Each venue has its own networks – the relationships between policy makers and influencers – so build trust and form alliances within networks.
  • Policymaking attention is often driven by changes in socioeconomic factors, or routine/ non-routine events, so be prepared to exploit the ‘windows of opportunity’ to present your solution during heightened attention to a policy problem.

Further, policy theories/ studies help us understand the context in which people make such choices. For example, consider the story that Kathryn Oliver and I tell about the role of evidence in policymaking environments:

If there are so many potential authoritative venues, devote considerable energy to finding where the ‘action’ is (and someone specific to talk to). Even if you find the right venue, you will not know the unwritten rules unless you study them intensely. Some networks are close-knit and difficult to access because bureaucracies have operating procedures that favour some sources of evidence. Research advocates can be privileged insiders in some venues and excluded completely in others. If your evidence challenges an existing paradigm, you need a persuasion strategy good enough to prompt a shift of attention to a policy problem and a willingness to understand that problem in a new way. You can try to find the right time to use evidence to exploit a crisis leading to major policy change, but the opportunities are few and chances of success low.  In that context, policy studies recommend investing your time over the long term – to build up alliances, trust in the messenger, knowledge of the system, and to seek ‘windows of opportunity’ for policy change – but offer no assurances that any of this investment will ever pay off

As described, this focus on the new policy sciences and synthesising insights helps explain why ‘the politics of evidence-based policymaking’ is equally important to civil servants (my occasional audience) as researchers (my usual audience).

To engage in skilled policy analysis, and give good advice, is to recognise the ways in which policymakers combine cognition/emotion to engage with evidence, and must navigate a complex policymaking environment when designing or selecting technically and politically feasible solutions. To give good advice is to recognise what you want policymakers to do, but also that they are not in control of the consequences.

From one story to many?

However, I tell these stories without my audience having the time to look further into each theory and its individual insights. If they do have a little more time, I go into the possible contribution of individual insights to debate.

For example, they adapt insights from psychology in different ways …

  • PET shows the overall effect of policymaker psychology on policy change: they combine cognition and emotion to pay disproportionate attention to a small number of issues (contributing to major change) and ignore the rest (contributing to ‘hyperincremental’ change).
  • The IAD focuses partly on the rules and practices that actors develop to build up trust in each other.
  • The ACF describes actors going into politics to turn their beliefs into policy, forming coalitions with people who share their beliefs, then often romanticising their own cause and demonising their opponents.
  • The NPF describes the relative impact of stories on audiences who use cognitive shortcuts to (for example) identify with a hero and draw a simple moral.
  • SCPD describes policymakers drawing on gut feeling to identify good and bad target populations.
  • Policy learning involves using cognition and emotion to acquire new knowledge and skills.

… even though the pace of change in psychological research often seems faster than the ways in which policy studies can incorporate new and reliable insights.

They also present different conceptions of the policymaking environment in which actors make choices. See this post for more on this discussion in relation to EBPM.

My not-brilliant conclusion is that:

  1. Policy theory/ policy studies has a lot to offer other disciplines and professions, particularly in field like EBPM in which we need to account for politics and, more importantly, policymaking systems, but
  2. Beware any policy theory story that presents the source literature as coherent and consistent.
  3. Rather, any story of the field involves a series of choices about what counts as a good theory and good insight.
  4. In other words, the exhortation to think more about what counts as ‘good evidence’ applies just as much to political science as any other.

Postscript: well, that is the last of the posts for my ANZOG talks. If I’ve done this properly, there should now be a loop of talks. It should be possible to go back to the first one and see it as a sequel to this one!

Or, for more on theory-informed policy analysis – in other words, where the ‘new policy sciences’ article is taking us – here is how I describe it to students doing a policy analysis paper (often for the first time).

Or, have a look at the earlier discussion of images of the policy process. You may have noticed that there is a different image in this post (knocked up in my shed at the weekend). It’s because I am experimenting with shapes. Does the image with circles look more relaxing? Does the hexagonal structure look complicated even though it is designed to simplify? Does it matter? I think so. People engage emotionally with images. They share them. They remember them. So, I need an image more memorable than the policy cycle.

Paul Cairney Brisbane EBPM New Policy Sciences 25.10.18

*I welcome suggestions on another word to describe almost-impossibly-hard

5 Comments

Filed under agenda setting, Evidence Based Policymaking (EBPM), Policy learning and transfer, Psychology Based Policy Studies, public policy

Evidence-based policymaking and the ‘new policy sciences’

Circle image policy process 24.10.18

I have given a series of talks to explain why we should think of ‘evidence-based policymaking’ as a myth or political slogan, not an ideal scenario or something to expect from policymaking in the real world. They usually involve encouraging framing and storytelling rather than expecting evidence to speak for itself, and rejecting the value of simple models like the policy cycle. I then put up an image of my own and encourage people to think about the implications of each concept:

SLIDE simple advice from hexagon image policy process 24.10.18

I describe the advice as simple-sounding and feasible at first glance, but actually a series of Herculean* tasks:

  • There are many policymakers and influencers spread across government, so find out where the action is, or the key venues in which people are making authoritative decisions.
  • Each venue has its own ‘institutions’ – the formal and written, or informal and unwritten rules of policymaking – so learn the rules of each venue in which you engage.
  • Each venue is guided by a fundamental set of ideas – as paradigms, core beliefs, monopolies of understanding – so learn that language.
  • Each venue has its own networks – the relationships between policy makers and influencers – so build trust and form alliances within networks.
  • Policymaking attention is often driven by changes in socioeconomic factors, or routine/ non-routine events, so be prepared to exploit the ‘windows of opportunity’ to present your solution during heightened attention to a policy problem.

In most cases, we don’t have time to discuss a more fundamental issue (at least for researchers using policy theory and political science concepts):

From where did these concepts come, and how well do we know them?

To cut a long story short, each concept represents its own literature: see these short explainers on the psychology of policymaking, actors spread across multi-level governance, institutions, networks, ideas, and socioeconomic factors/ events. What the explainers don’t really project is the sense of debate within the literature about how best to conceptualise each concept. You can pick up their meaning in a few minutes but would need a few years to appreciate the detail and often-fundamental debate.

Ideally, we would put all of the concepts together to help explain policymaker choice within a complex policymaking environment (how else could I put up the image and present is as one source of accumulated wisdom from policy studies?). Peter John describes such accounts as ‘synthetic’. I have also co-authored work with Tanya Heikkila – in 2014 and 2017 to compare the different ways in which ‘synthetic’ theories conceptualise the policy process. However, note the difficulty of putting together a large collection of separate and diverse literatures into one simple model (e.g. while doing a PhD).

The new policy sciences

More recently, in the ‘new policy sciences’, Chris Weible and I present a more provocative story of these efforts, in which we advocate:

  • a return to Lasswell’s vision of combining policy analysis (to recommend policy change) and policy theory (to explain policy change), but
  • focusing on a far larger collection of actors (beyond a small group at the centre),
  • recognising new developments in studies of the psychology of policymaker choice, and
  • building into policy analysis the recognition that any policy solution is introduced in a complex policymaking environment over which no-one has control.

This focus on psychology is not new …

  • PET shows the overall effect of policymaker psychology on policy change: they combine cognition and emotion to pay disproportionate attention to a small number of issues (contributing to major change) and ignore the rest (contributing to ‘hyperincremental’ change).
  • The IAD focuses partly on the rules and practices that actors develop to build up trust in each other.
  • The ACF describes actors going into politics to turn their beliefs into policy, forming coalitions with people who share their beliefs, then often romanticising their own cause and demonising their opponents.
  • The NPF describes the relative impact of stories on audiences who use cognitive shortcuts to (for example) identify with a hero and draw a simple moral.
  • SCPD describes policymakers drawing on gut feeling to identify good and bad target populations.
  • Policy learning involves using cognition and emotion to acquire new knowledge and skills.

… but the pace of change in psychological research often seems faster than the ways in which policy studies can incorporate new and reliable insights.

Perhaps more importantly, policy studies help us understand the context in which people make such choices. For example, consider the story that Kathryn Oliver and I tell about the role of evidence in policymaking environments:

If there are so many potential authoritative venues, devote considerable energy to finding where the ‘action’ is (and someone specific to talk to). Even if you find the right venue, you will not know the unwritten rules unless you study them intensely. Some networks are close-knit and difficult to access because bureaucracies have operating procedures that favour some sources of evidence. Research advocates can be privileged insiders in some venues and excluded completely in others. If your evidence challenges an existing paradigm, you need a persuasion strategy good enough to prompt a shift of attention to a policy problem and a willingness to understand that problem in a new way. You can try to find the right time to use evidence to exploit a crisis leading to major policy change, but the opportunities are few and chances of success low.  In that context, policy studies recommend investing your time over the long term – to build up alliances, trust in the messenger, knowledge of the system, and to seek ‘windows of opportunity’ for policy change – but offer no assurances that any of this investment will ever pay off

Then, have a look at this discussion of ‘synthetic’ policy theories, designed to prompt people to consider how far they would go to get their evidence into policy.

Theory-driven policy analysis

As described, this focus on the new policy sciences helps explain why ‘the politics of evidence-based policymaking’ is equally important to civil servants (my occasional audience) as researchers (my usual audience).

To engage in skilled policy analysis, and give good advice, is to recognise the ways in which policymakers combine cognition/emotion to engage with evidence, and must navigate a complex policymaking environment when designing or selecting technically and politically feasible solutions. To give good advice is to recognise what you want policymakers to do, but also that they are not in control of the consequences.

Epilogue

Well, that is the last of the posts for my ANZOG talks. If I’ve done this properly, there should now be a loop of talks. It should be possible to go back to the first one in Auckland and see it as a sequel to this one in Brisbane!

Or, for more on theory-informed policy analysis – in other words, where the ‘new policy sciences’ article is taking us – here is how I describe it to students doing a policy analysis paper (often for the first time).

Or, have a look at the earlier discussion of images of the policy process. You may have noticed that there is a different image in this post (knocked up in my shed at the weekend). It’s because I am experimenting with shapes. Does the image with circles look more relaxing? Does the hexagonal structure look complicated even though it is designed to simplify? Does it matter? I think so. People engage emotionally with images. They share them. They remember them. So, I need an image more memorable than the policy cycle.

 

Paul Cairney Brisbane EBPM New Policy Sciences 25.10.18

 

 

*I welcome suggestions on another word to describe almost-impossibly-hard

2 Comments

Filed under agenda setting, Evidence Based Policymaking (EBPM), Policy learning and transfer, Psychology Based Policy Studies, public policy, Storytelling

Theory and Practice: How to Communicate Policy Research beyond the Academy

Notes (and audio) for my first talk at the University of Queensland, Wednesday 24th October, 12.30pm, Graduate Centre, room 402.

Here is the powerpoint that I tend to use to inform discussions with civil servants (CS). I first used it for discussion with CS in the Scottish and UK governments, followed by remarkably similar discussions in parts of New Zealand and Australian government. Partly, it provides a way into common explanations for gaps between the supply of, and demand for, research evidence. However, it also provides a wider context within which to compare abstract and concrete reasons for those gaps, which inform a discussion of possible responses at individual, organisational, and systemic levels. Some of the gap is caused by a lack of effective communication, but we should also discuss the wider context in which such communication takes place.

I begin by telling civil servants about the message I give to academics about why policymakers might ignore their evidence:

  1. There are many claims to policy relevant knowledge.
  2. Policymakers have to ignore most evidence.
  3. There is no simple policy cycle in which we all know at what stage to provide what evidence.

slide 3 24.10.18

In such talks, I go into different images of policymaking, comparing the simple policy cycle with images of ‘messy’ policymaking, then introducing my own image which describes the need to understand the psychology of choice within a complex policymaking environment.

Under those circumstances, key responses include:

  • framing evidence in terms of the ways in which your audience understands policy problems
  • engaging in networks to identify and exploit the right time to act, and
  • venue shopping to find sympathetic audiences in different parts of political systems.

However, note the context of those discussions. I tend to be speaking with scientific researcher audiences to challenge some preconceptions about: what counts as good evidence, how much evidence we can reasonably expect policymakers to process, and how easy it is to work out where and when to present evidence. It’s generally a provocative talk, to identify the massive scale of the evidence-to-policy task, not a simple ‘how to do it’ guide.

In that context, I suggest to civil servants that many academics might be interested in more CS engagement, but might be put off by the overwhelming scale of their task, and – even if they remained undeterred – would face some practical obstacles:

  1. They may not know where to start: who should they contact to start making connections with policymakers?
  2. The incentives and rewards for engagement may not be clear. The UK’s ‘impact’ agenda has changed things, but not to the extent that any engagement is good engagement. Researchers need to tell a convincing story that they made an impact on policy/ policymakers with their published research, so there is a notional tipping point of engagement in which it reaches a scale that makes it worth doing.
  3. The costs are clearer. For example, any time spent doing engagement is time away from writing grant proposals and journal articles (in other words, the things that still make careers).
  4. The rewards and costs are not spread evenly. Put most simply, white male professors may have the most opportunities and face the fewest penalties for engagement in policymaking and social media. Or, the opportunities and rewards may vary markedly by discipline. In some, engagement is routine. In others, it is time away from core work.

In that context, I suggest that CS should:

  • provide clarity on what they expect from academics, and when they need information
  • describe what they can offer in return (which might be as simple as a written and signed acknowledgement of impact, or formal inclusion on an advisory committee).
  • show some flexibility: you may have a tight deadline, but can you reasonably expect an academic to drop what they are doing at short notice?
  • Engage routinely with academics, to help form networks and identify the right people you need at the right time

These introductory discussions provide a way into common descriptions of the gap between academic and policymaker:

  • Technical languages/ jargon to describe their work
  • Timescales to supply and demand information
  • Professional incentives (such as to value scientific novelty in academia but evidential synthesis in government
  • Comfort with uncertainty (often, scientists project relatively high uncertainty and don’t want to get ahead of the evidence; often policymakers need to project certainty and decisiveness)
  • Assessments of the relative value of scientific evidence compared to other forms of policy-relevant information
  • Assessments of the role of values and beliefs (some scientists want to draw the line between providing evidence and advice; some policymakers want them to go much further)

To discuss possible responses, I use the European Commission Joint Research Centre’s ‘knowledge management for policy’ project in which they identify the 8 core skills of organisations bringing together the suppliers and demanders of policy-relevant knowledge

Figure 1

However, I also use the following table to highlight some caution about the things we can achieve with general skills development and organisational reforms. Sometimes, the incentives to engage will remain low. Further, engagement is no guarantee of agreement.

In a nutshell, the table provides three very different models of ‘evidence-informed policymaking’ when we combine political choices about what counts as good evidence, and what counts as good policymaking (discussed at length in teaching evidence-based policy to fly). Discussion and clearer communication may help clarify our views on what makes a good model, but I doubt it will produce any agreement on what to do.

Table 1 3 ideal types of EBBP

In the latter part of the talk, I go beyond that powerpoint into two broad examples of practical responses:

  1. Storytelling

The Narrative Policy Framework describes the ‘science of stories’: we can identify stories with a 4-part structure (setting, characters, plot, moral) and measure their relative impact.  Jones/ Crow and Crow/Jones provide an accessible way into these studies. Also look at Davidson’s article on the ‘grey literature’ as a rich source of stories on stories.

On one hand, I think that storytelling is a great possibility for researchers: it helps them produce a core – and perhaps emotionally engaging – message that they can share with a wider audience. Indeed, I’d see it as an extension of the process that academics are used to: identifying an audience and framing an argument according to the ways in which that audience understands the world.

On the other hand, it is important to not get carried away by the possibilities:

  • My reading of the NPF empirical work is that the most impactful stories are reinforcing the beliefs of the audience – to mobilise them to act – not changing their minds.
  • Also look at the work of the Frameworks Institute which experiments with individual versus thematic stories because people react to them in very different ways. Some might empathise with an individual story; some might judge harshly. For example, they discusse stories about low income families and healthy eating, in which they use the theme of a maze to help people understand the lack of good choices available to people in areas with limited access to healthy food.

See: Storytelling for Policy Change: promise and problems

  1. Evidence for advocacy

The article I co-authored with Oxfam staff helps identify the lengths to which we might think we have to go to maximise the impact of research evidence. Their strategies include:

  1. Identifying the policy change they would like to see.
  2. Identifying the powerful actors they need to influence.
  3. A mixture of tactics: insider, outsider, and supporting others by, for example, boosting local civil society organisations.
  4. A mix of ‘evidence types’ for each audience

oxfam table 2

  1. Wider public campaigns to address the political environment in which policymakers consider choices
  2. Engaging stakeholders in the research process (often called the ‘co-production of knowledge’)
  3. Framing: personal stories, ‘killer facts’, visuals, credible messenger
  4. Exploiting ‘windows of opportunity’
  5. Monitoring, learning, trial and error

In other words, a source of success stories may provide a model for engagement or the sense that we need to work with others to engage effectively. Clear communication is one thing. Clear impact at a significant scale is another.

See: Using evidence to influence policy: Oxfam’s experience

 

 

 

 

 

 

 

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Filed under agenda setting, Evidence Based Policymaking (EBPM)

Taking lessons from policy theory into practice: 3 examples

Notes for ANZSOG/ ANU Crawford School/ UNSW Canberra workshop. Powerpoint here. The recording of the lecture (skip to 2m30) and Q&A is here (right click to download mp3 or dropbox link):

The context for this workshop is the idea that policy theories could be more helpful to policymakers/ practitioners if we could all communicate more effectively with each other. Academics draw general and relatively abstract conclusions from multiple cases. Practitioners draw very similar conclusions from rich descriptions of direct experience in a smaller number of cases. How can we bring together their insights and use a language that we all understand? Or, more ambitiously, how can we use policy theory-based insights to inform the early career development training that civil servants and researchers receive?

The first step is to translate policy theories into a non-technical language by trying to speak with an audience beyond our immediate peers (see for example Practical Lessons from Policy Theories).

However, translation is not enough. A second crucial step is to consider how policymakers and practitioners are likely to make sense of theoretical insights when they apply them to particular aims or responsibilities. For example:

  1. Central government policymakers may accept the descriptive accuracy of policy theories emphasising limited central control, but not the recommendation that they should let go, share power, and describe their limits to the public.
  2. Scientists may accept key limitations to ‘evidence based policymaking’ but reject the idea that they should respond by becoming better storytellers or more manipulative operators.
  3. Researchers and practitioners struggle to resolve hard choices when combining evidence and ‘coproduction’ while ‘scaling up’ policy interventions. Evidence choice is political choice. Can we do more than merely encourage people to accept this point?

I discuss these examples below because they are closest to my heart (especially example 1). Note throughout that I am presenting one interpretation about: (1) the most promising insights, and (2) their implications for practice. Other interpretations of the literature and its implications are available. They are just a bit harder to find.

Example 1: the policy cycle endures despite its descriptive inaccuracy

cycle

The policy cycle does not describe and explain the policy process well:

  • If we insist on keeping the cycle metaphor, it is more accurate to see the process as a huge set of policy cycles that connect with each other in messy and unpredictable ways.
  • The cycle approach also links strongly to the idea of ‘comprehensive rationality’ in which a small group of policymakers and analysts are in full possession of the facts and full control of the policy process. They carry out their aims through a series of stages.

Policy theories provide more descriptive and explanatory usefulness. Their insights include:

  • Limited choice. Policymakers inherit organisations, rules, and choices. Most ‘new’ choice is a revision of the old.
  • Limited attention. Policymakers must ignore almost all of the policy problems for which they are formally responsible. They pay attention to some, and delegate most responsibility to civil servants. Bureaucrats rely on other actors for information and advice, and they build relationships on trust and information exchange.
  • Limited central control. Policy may appear to be made at the ‘top’ or in the ‘centre’, but in practice policymaking responsibility is spread across many levels and types of government (many ‘centres’). ‘Street level’ actors make policy as they deliver. Policy outcomes appear to ‘emerge’ locally despite central government attempts to control their fate.
  • Limited policy change. Most policy change is minor, made and influenced by actors who interpret new evidence through the lens of their beliefs. Well-established beliefs limit the opportunities of new solutions. Governments tend to rely on trial-and-error, based on previous agreements, rather than radical policy change based on a new agenda. New solutions succeed only during brief and infrequent windows of opportunity.

However, the cycle metaphor endures because:

  • It provides a simple model of policymaking with stages that map onto important policymaking functions.
  • It provides a way to project policymaking to the public. You know how we make policy, and that we are in charge, so you know who to hold to account.

In that context, we may want to be pragmatic about our advice:

  1. One option is via complexity theory, in which scholars generally encourage policymakers to accept and describe their limits:
  • Accept routine error, reduce short-term performance management, engage more in trial and error, and ‘let go’ to allow local actors the flexibility to adapt and respond to their context.
  • However, would a government in the Westminster tradition really embrace this advice? No. They need to balance (a) pragmatic policymaking, and (b) an image of governing competence.
  1. Another option is to try to help improve an existing approach.

Further reading (blog posts):

The language of complexity does not mix well with the language of Westminster-style accountability

Making Sense of Policymaking: why it’s always someone else’s fault and nothing ever changes

Two stories of British politics: the Westminster model versus Complex Government

Example 2: how to deal with a lack of ‘evidence based policymaking’

I used to read many papers on tobacco policy, with the same basic message: we have the evidence of tobacco harm, and evidence of which solutions work, but there is an evidence-policy gap caused by too-powerful tobacco companies, low political will, and pathological policymaking. These accounts are not informed by theories of policymaking.

I then read Oliver et al’s paper on the lack of policy theory in health/ environmental scholarship on the ‘barriers’ to the use of evidence in policy. Very few articles rely on policy concepts, and most of the few rely on the policy cycle. This lack of policy theory is clear in their description of possible solutions – better communication, networking, timing, and more science literacy in government – which does not describe well the need to respond to policymaker psychology and a complex policymaking environment.

So, I wrote The Politics of Evidence-Based Policymaking and one zillion blog posts to help identify the ways in which policy theories could help explain the relationship between evidence and policy.

Since then, the highest demand to speak about the book has come from government/ public servant, NGO, and scientific audiences outside my discipline. The feedback is generally that: (a) the book’s description sums up their experience of engagement with the policy process, and (b) maybe it opens up discussion about how to engage more effectively.

But how exactly do we turn empirical descriptions of policymaking into practical advice?

For example, scientist/ researcher audiences want to know the answer to a question like: Why don’t policymakers listen to your evidence? and so I focus on three conversation starters:

  1. they have a broader view on what counts as good evidence (see ANZSOG description)
  2. they have to ignore almost all information (a nice way into bounded rationality and policymaker psychology)
  3. they do not understand or control the process in which they seek to use evidence (a way into ‘the policy process’)

Cairney 2017 image of the policy process

We can then consider many possible responses in the sequel What can you do when policymakers ignore your evidence?

Examples include:

  • ‘How to do it’ advice. I compare tips for individuals (from experienced practitioners) with tips based on policy concepts. They are quite similar-looking tips – e.g. find out where the action is, learn the rules, tell good stories, engage allies, seek windows of opportunity – but I describe mine as 5 impossible tasks!
  • Organisational reform. I describe work with the European Commission Joint Research Centre to identify 8 skills or functions of an organisation bringing together the supply/demand of knowledge.
  • Ethical dilemmas. I use key policy theories to ask people how far they want to go to privilege evidence in policy. It’s fun to talk about these things with the type of scientist who sees any form of storytelling as manipulation.

Further reading:

Is Evidence-Based Policymaking the same as good policymaking?

A 5-step strategy to make evidence count

Political science improves our understanding of evidence-based policymaking, but does it produce better advice?

Principles of science advice to government: key problems and feasible solutions

Example 3: how to encourage realistic evidence-informed policy transfer

This focus on EBPM is useful context for discussions of ‘policy learning’ and ‘policy transfer’, and it was the focus of my ANZOG talk entitled (rather ambitiously) ‘teaching evidence-based policy to fly’.

I’ve taken a personal interest in this one because I’m part of a project – called IMAJINE – in which we have to combine academic theory and practical responses. We are trying to share policy solutions across Europe rather than explain why few people share them!

For me, the context is potentially overwhelming:

So, when we start to focus on sharing lessons, we will have three things to discover:

  1. What is the evidence for success, and from where does it come? Governments often project success without backing it up.
  2. What story do policymakers tell about the problem they are trying to solve, the solutions they produced, and why? Two different governments may be framing and trying to solve the same problem in very different ways.
  3. Was the policy introduced in a comparable policymaking system? People tend to focus on political system comparability (e.g. is it unitary or federal?), but I think the key is in policymaking system comparability (e.g. what are the rules and dominant ideas?).

To be honest, when one of our external assessors asked me how well I thought I would do, we both smiled because the answer may be ‘not very’. In other words, the most practical lesson may be the hardest to take, although I find it comforting: the literature suggests that policymakers might ignore you for 20 years then suddenly become very (but briefly) interested in your work.

 

The slides are a bit wonky because I combined my old ppt to the Scottish Government with a new one for UNSW Paul Cairney ANU Policy practical 22 October 2018

I wanted to compare how I describe things to (1) civil servants (2) practitioners/ researcher (3) me, but who has the time/ desire to listen to 3 powerpoints in one go? If the answer is you, let me know and we’ll set up a Zoom call.

2 Comments

Filed under agenda setting, Evidence Based Policymaking (EBPM), IMAJINE, Policy learning and transfer

Prevention is better than cure, so why aren’t we doing more of it?

This post provides a generous amount of background for my ANZSOG talk Prevention is better than cure, so why aren’t we doing more of it? If you read all of it, it’s a long read. If not, it’s a short read before the long read. Here is the talk’s description:

‘Does this sound familiar? A new government comes into office, promising to shift the balance in social and health policy from expensive remedial, high dependency care to prevention and early intervention. They commit to better policy-making; they say they will join up policy and program delivery, devolving responsibility to the local level and focusing on long term outcomes rather than short term widgets; and that they will ensure policy is evidence-based.  And then it all gets too hard, and the cycle begins again, leaving some exhausted and disillusioned practitioners in its wake. Why does this happen repeatedly, across different countries and with governments of different persuasions, even with the best will in the world?’ 

  • You’ll see from the question that I am not suggesting that all prevention or early intervention policies fail. Rather, I use policy theories to provide a general explanation for a major gap between the (realistic) expectations expressed in prevention strategies and the actual outcomes. We can then talk about how to close that gap.
  • You’ll also see the phrase ‘even with the best will in the world’, which I think is key to this talk. No-one needs me to rehearse the usually-vague and often-stated ways to explain failed prevention policies, including the ‘wickedness’ of policy problems, or the ‘pathology’ of public policy. Rather, I show that such policies may ‘fail’ even when there is wide and sincere cross-party agreement about the need to shift from reactive to more prevention policy design. I also suggest that the general explanation for failure – low ‘political will’ – is often damaging to the chances for future success.
  • Let’s start by defining prevention policy and policymaking.

When engaged in ‘prevention’, governments seek to:

  1. Reform policy.

Prevention policy is really a collection of policies designed to intervene as early as possible in people’s lives to improve their wellbeing and reduce inequalities and/or demand for acute services. The aim is to move from reactive to preventive public services, intervening earlier in people’s lives to address a wide range of longstanding problems – including crime and anti-social behaviour, ill health and unhealthy behaviour, low educational attainment, unemployment and low employability – before they become too severe.

  1. Reform policymaking.

Preventive policymaking describes the ways in which governments reform their practices to support prevention policy, including a commitment to:

  • ‘join up’ government departments and services to solve ‘wicked problems’ that transcend one area
  • give more responsibility for service design to local public bodies, stakeholders, ‘communities’ and service users produce long term aims for outcomes, and
  • reduce short term performance targets in favour of long term outcomes agreements.
  1. Ensure that policy is ‘evidence based’.

Three general reasons why ‘prevention’ policies never seem to succeed.

  1. Policymakers don’t know what prevention means.

They express a commitment to prevention before defining it fully. When they start to make sense of prevention, they find out how difficult it is to pursue, and how many controversial choices it involves (see also uncertainty versus ambiguity)

  1. They engage in a policymaking system that is too complex to control.

They try to share responsibility with many actors and coordinate action to direct policy outcomes, without the ability to design those relationships and control policy outcomes.

Yet, they also need to demonstrate to the electorate that they are in control, and find out how difficult it is to localise and centralise policy.

  1. They are unable and unwilling to produce ‘evidence based policymaking’.

Policymakers seek cognitive shortcuts (and their organisational equivalents) to gather enough information to make ‘good enough’ decisions. When they seek evidence on prevention, they find that it is patchy, inconclusive, often counter to their beliefs, and not a ‘magic bullet’ to help justify choices.

Throughout this process, their commitment to prevention policy can be sincere but unfulfilled. They do not articulate fully what prevention means or appreciate the scale of their task. When they try to deliver prevention strategies, they face several problems that, on their own, would seem daunting. Many of the problems they seek to ‘prevent’ are ‘wicked’, or difficult to define and seemingly impossible to solve, such as poverty, unemployment, low quality housing and homelessness, crime, and health and education inequalities. They face stark choices on how far they should go to shift the balance between state and market, redistribute wealth and income, distribute public resources, and intervene in people’s lives to change their behaviour and ways of thinking. Their focus on the long term faces major competition from more salient short-term policy issues that prompt them to maintain ‘reactive’ public services. Their often-sincere desire to ‘localise’ policymaking often gives way to national electoral politics, in which central governments face pressure to make policy from the ‘top’ and be decisive. Their pursuit of ‘evidence based’ policymaking often reveals a lack of evidence about which policy interventions work and the extent to which they can be ‘scaled up’ successfully.

These problems will not be overcome if policy makers and influencers misdiagnose them

  • If policy influencers make the simplistic assumption that this problem is caused by low political they will provide bad advice.
  • If new policymakers truly think that the problem was the low commitment and competence of their predecessors, they will begin with the same high hopes about the impact they can make, only to become disenchanted when they see the difference between their abstract aims and real world outcomes.
  • Poor explanation of limited success contributes to the high potential for (a) an initial period of enthusiasm and activity, replaced by (b) disenchantment and inactivity, and (c) for this cycle to be repeated without resolution.

Let’s add more detail to these general explanations:

1. What makes prevention so difficult to define?

When viewed as a simple slogan, ‘prevention’ seems like an intuitively appealing aim. It can generate cross-party consensus, bringing together groups on the ‘left’, seeking to reduce inequalities, and on the ‘right’, seeking to reduce economic inactivity and the cost of services.

Such consensus is superficial and illusory. When making a detailed strategy, prevention is open to many interpretations by many policymakers. Imagine the many types of prevention policy and policymaking that we could produce:

  1. What problem are we trying to solve?

Prevention policymaking represents a heroic solution to several crises: major inequalities, underfunded public services, and dysfunctional government.

  1. On what measures should we focus?

On which inequalities should we focus primarily? Wealth, occupation, income, race, ethnicity, gender, sexuality, disability, mental health.

On which measures of inequality? Economic, health, healthy behaviour, education attainment, wellbeing, punishment.

  1. On what solution should we focus?

To reduce poverty and socioeconomic inequalities, improve national quality of life, reduce public service costs, or increase value for money

  1. Which ‘tools’ or policy instruments should we use?

Redistributive policies to address ‘structural’ causes of poverty and inequality?

Or, individual-focused policies to: (a) boost the mental ‘resilience’ of public service users, (b) oblige, or (c) exhort people to change behaviour.

  1. How do we intervene as early as possible in people’s lives?

Primary prevention. Focus on the whole population to stop a problem occurring by investing early and/or modifying the social or physical environment. Akin to whole-population immunizations.

Secondary prevention. Focus on at-risk groups to identify a problem at a very early stage to minimise harm.

Tertiary prevention. Focus on affected groups to stop a problem getting worse.

  1. How do we pursue ‘evidence based policymaking’? 3 ideal-types

Using randomised control trials and systematic review to identify the best interventions?

Storytelling to share best governance practice?

‘Improvement’ methods to experiment on a small scale and share best practice?

  1. How does evidence gathering connect to long-term policymaking?

Does a national strategy drive long-term outcomes?

Does central government produce agreements with or targets for local authorities?

  1. Is preventive policymaking a philosophy or a profound reform process?

How serious are national governments – about localism, service user-driven public services, and joined up or holistic policymaking – when their elected policymakers are held to account for outcomes?

  1. What is the nature of state intervention?

It may be punitive or supportive. See: How would Lisa Simpson and Monty Burns make progressive social policy?

2.     Making ‘hard choices’: what problems arise when politics meets policymaking?

When policymakers move from idiom and broad philosophy towards specific policies and practices, they find a range of obstacles, including:

The scale of the task becomes overwhelming, and not suited to electoral cycles.

Developing policy and reforming policymaking takes time, and the effect may take a generation to see.

There is competition for policymaking resources such as attention and money.

Prevention is general, long-term, and low salience. It competes with salient short-term problems that politicians feel compelled to solve first.

Prevention is akin to capital investment with no guarantee of a return. Reductions in funding ‘fire-fighting’, ‘frontline’ services to pay for prevention initiatives, are hard to sell. Governments invest in small steps, and investment is vulnerable when money is needed quickly to fund public service crises.

The benefits are difficult to measure and see.

Short-term impacts are hard to measure, long-term impacts are hard to attribute to a single intervention, and prevention does not necessarily save money (or provide ‘cashable’ savings’).

Reactive policies have a more visible impact, such as to reduce hospital waiting times or increase the number of teachers or police officers.

Problems are ‘wicked’.

Getting to the ‘root causes’ of problems is not straightforward; policymakers often have no clear sense of the cause of problems or effect of solutions. Few aspects of prevention in social policy resemble disease prevention, in which we know the cause of many diseases, how to screen for them, and how to prevent them in a population.

Performance management is not conducive to prevention.

Performance management systems encourage public sector managers to focus on their services’ short-term and measurable targets over shared aims with public service partners or the wellbeing of their local populations.

Performance management is about setting priorities when governments have too many aims to fulfil. When central governments encourage local governing bodies to form long-term partnerships to address inequalities and meet short-term targets, the latter come first.

Governments face major ethical dilemmas.

Political choices co-exist with normative judgements concerning the role of the state and personal responsibility, often undermining cross-party agreement.

One aspect of prevention may undermine the other.

A cynical view of prevention initiatives is that they represent a quick political fix rather than a meaningful long-term solution:

  • Central governments describe prevention as the solution to public sector costs while also delegating policymaking responsibility to, and reducing the budgets of, local public bodies.
  • Then, public bodies prioritise their most pressing statutory responsibilities.

Someone must be held to account.

If everybody is involved in making and shaping policy, it becomes unclear who can be held to account over the results. This outcome is inconsistent with Westminster-style democratic accountability in which we know who is responsible and therefore who to praise or blame.

3.      ‘The evidence’ is not a ‘magic bullet’

In a series of other talks, I identify the reasons why ‘evidence based policymaking’ (EBPM) does not describe the policy process well.

Elsewhere, I also suggest that it is more difficult for evidence to ‘win the day’ in the broad area of prevention policy compared to the more specific field of tobacco control.

Generally speaking, a good simple rule about EBPM is that there is never a ‘magic bullet’ to take the place of judgement. Politics is about making choices which benefit some while others lose out. You can use evidence to help clarify those choices, but not produce a ‘technical’ solution.

A further rule with ‘wicked’ problems is that the evidence is not good enough even to generate clarity about the cause of the problem. Or, you simply find out things you don’t want to hear.

Early intervention in ‘families policies’ seems to be a good candidate for the latter, for three main reasons:

  1. Very few interventions live up to the highest evidence standards

There are two main types of relevant ‘evidence based’ interventions in this field.

The first are ‘family intervention projects’ (FIPs). They generally focus on low income, often lone parent, families at risk of eviction linked to factors such as antisocial behaviour, and provide two forms of intervention:

  • intensive 24/7 support, including after school clubs for children and parenting skills classes, and treatment for addiction or depression in some cases, in dedicated core accommodation with strict rules on access and behaviour
  • an outreach model of support and training.

The evidence of success comes from evaluation plus a counterfactual: this intervention is expensive, but we think that it would have cost far more money and heartache if we had not intervened. There is generally no randomised control trial (RCT) to establish the cause of improved outcomes, or demonstrate that those outcomes would not have happened without this intervention.

The second are projects imported from other countries (primarily the US and Australia) based on their reputation for success built on RCT evidence. There is more quantitative evidence of success, but it is still difficult to know if the project can be transferred effectively and if its success can be replicated in another country with a very different political drivers, problems, and services.

2. The evidence on ‘scaling up’ for primary prevention is relatively weak

Kenneth Dodge (2009) sums up a general problem:

  • there are few examples of taking effective specialist projects ‘to scale’
  • there are major issues around ‘fidelity’ to the original project when you scale up (including the need to oversee a major expansion in well-trained practitioners)
  • it is difficult to predict the effect of a programme, which showed promise when applied to one population, to a new and different population.

3. The evidence on secondary early intervention is also weak

This point about different populations with different motivations is demonstrated in a more recent (published 2014) study by Stephen Scott et al of two Incredible Years interventions – to address ‘oppositional defiant disorder symptoms and antisocial personality character traits’ in children aged 3-7 (for a wider discussion of such programmes see the Early Intervention Foundation’s Foundations for life: what works to support parent child interaction in the early years?).

They highlight a classic dilemma in early intervention: the evidence of effectiveness is only clear when children have been clinically referred (‘indicated approach’), but unclear when children have been identified as high risk using socioeconomic predictors (‘selective approach’):

An indicated approach is simpler to administer, as there are fewer children with severe problems, they are easier to identify, and their parents are usually prepared to engage in treatment; however, the problems may already be too entrenched to treat. In contrast, a selective approach targets milder cases, but because problems are less established, whole populations have to be screened and fewer cases will go on to develop serious problems.

For our purposes, this may represent the most inconvenient form of evidence on early intervention: you can intervene early on the back of very limited evidence of likely success, or have a far higher likelihood of success when you intervene later, when you are running out of time to call it ‘early intervention’.

Conclusion: vague consensus is no substitute for political choice

Governments begin with the sense that they have found the solution to many problems, only to find that they have to make and defend highly ‘political’ choices.

For example, see the UK government’s ‘imaginative’ use of evidence to make families policy. In a nutshell, it chose to play fast and loose with evidence, and demonise 117000 families, to provide political cover to a redistribution of resources to family intervention projects.

We can, with good reason, object to this style of politics. However, we would also have to produce a feasible alternative.

For example, the Scottish Government has taken a different approach (perhaps closer to what one might often expect in New Zealand), but it still needs to produce and defend a story about its choices, and it faces almost the same constraints as the UK. It’s self-described ‘decisive shift’ to prevention was no a decisive shift to prevention.

Overall, prevention is no different from any other policy area, except that it has proven to be much more complicated and difficult to sustain than most others. Prevention is part of an excellent idiom but not a magic bullet for policy problems.

Further reading:

Prevention

See also

What do you do when 20% of the population causes 80% of its problems? Possibly nothing.

Early intervention policy, from ‘troubled families’ to ‘named persons’: problems with evidence and framing ‘valence’ issues

 

 

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Teaching evidence based policy to fly: how to deal with the politics of policy learning and transfer

This post provides (a generous amount of) background for my ANZSOG talk Teaching evidence based policy to fly: transferring sound policies across the world.

The event’s description sums up key conclusions in the literature on policy learning and policy transfer:

  1. technology and ‘entrepreneurs’ help ideas spread internationally, and domestic policymakers can use them to be more informed about global policy innovation, but
  2. there can be major unintended consequences to importing ideas, such as the adoption of policy solutions with poorly-evidenced success, or a broader sense of failed transportation caused by factors such as a poor fit between the aims of the exporter/importer.

In this post, I connect these conclusions to broader themes in policy studies, which suggest that:

  1. policy learning and policy transfer are political processes, not ‘rational’ or technical searches for information
  2. the use of evidence to spread policy innovation requires two interconnected choices: what counts as good evidence, and what role central governments should play.
  3. the following ’11 question guide’ to evidence based policy transfer serves more as a way to reflect than a blueprint for action.

As usual, I suggest that we focus less on how we think we’d like to do it, and more on how people actually do it.

anzog auckland transfer ad

Policy transfer describes the use of evidence about policy in one political system to help develop policy in another. Taken at face value, it sounds like a great idea: why would a government try to reinvent the wheel when another government has shown how to do it?

Therefore, wouldn’t it be nice if I turned up to the lecture, equipped with a ‘blueprint’ for ‘evidence based’ policy transfer, and declared how to do it in a series of realistic and straightforward steps? Unfortunately, there are three main obstacles:

  1. ‘Evidence based’ is a highly misleading description of the use of information in policy.
  2. To transfer a policy blueprint completely, in this manner, would require all places and contexts to be the same, and for the policy process to be technocratic and apolitical.
  3. There are general academic guides on how to learn lessons from others systematically – such as Richard Rose’s ‘practical guide’  – but most academic work on learning and transfer does not suggest that policymakers follow this kind of advice.

Rose 10 lessons rotated

Instead, policy learning is a political process – involving the exercise of power to determine what and how to learn – and it is difficult to separate policy transfer from the wider use of evidence and ideas in policy processes.

Let’s take each of these points in turn, before reflecting on their implications for any X-step guide:

3 reasons why ‘evidence based’ does not describe policymaking

In a series of ANZSOG talks on ‘evidence based policymaking’ (EBPM), I describe three main factors, all of which are broadly relevant to transfer:

  1. There are many forms of policy-relevant evidence and few policymakers adhere to a strict ‘hierarchy’ of knowledge.

Therefore, it is unclear how one government can, or should, generate evidence of another government’s policy success.

  1. Policymakers must find ways to ignore most evidence – such as by combining ‘rational’ and ‘irrational’ cognitive shortcuts – to be able to act quickly.

The generation of policy transfer lessons is a highly political process in which actors adapt to this need to prioritise information while competing with each other. They exercise power to: prioritise some information and downplay the rest, define the nature of the policy problem, and evaluate the success of another government’s solutions. There is a strong possibility that policymakers will import policy solutions without knowing if, and why, they were successful.

  1. They do not control the policy process in which they engage.

We should not treat ‘policy transfer’ as separate from the policy process in which policymakers and influencers engage. Rather, the evidence of international experience competes with many other sources of ideas and evidence within a complex policymaking system.

The literature on ‘policy learning’ tells a similar story

Studies of the use of evaluation evidence (perhaps to answer the question: was this policy successful?) have long described policymakers using the research process for many different purposes, from short term problem-solving and long-term enlightenment, to putting off decisions or using evidence cynically to support an existing policy.

We should therefore reject the temptation to (a) equate ‘policy learning’ with a simplistic process that we might associate with teachers transmitting facts to children, or (b) assume that adults simply change their beliefs when faced with new evidence. Rather, Dunlop and Radaelli describe policy learning as a political process in the following ways:

1.It is collective and rule-bound

Individuals combine cognition and emotion to process information, in organisations with rules that influence their motive and ability to learn, and in wider systems, in which many actors cooperate and compete to establish the rules of evidence gathering and analysis, or policymaking environments that constrain or facilitate their action.

2.’Evidence based’ is one of several types of policy learning

  • Epistemic. Primarily by scientific experts transmitting knowledge to policymakers.
  • Reflection. Open dialogue to incorporate diverse forms of knowledge and encourage cooperation.
  • Bargaining. Actors learn how to cooperate and compete effectively.
  • Hierarchy. Actors with authority learn how to impose their aims; others learn the limits to their discretion.

3.The process can be ‘dysfunctional’: driven by groupthink, limited analysis, and learning how to dominate policymaking, not improve policy.

Their analysis can produce relevant take-home points such as:

  • Experts will be ineffective if they assume that policy learning is epistemic. The assumption will leave them ill-prepared to deal with bargaining.
  • There is more than one legitimate way to learn, such as via deliberative processes that incorporate more perspectives and forms of knowledge.

What does the literature on transfer tell us?

‘Policy transfer’ can describe a spectrum of activity:

  • driven voluntarily, by a desire to learn from the story of another government’s policy’s success. In such cases, importers use shortcuts to learning, such as by restricting their search to systems with which they have something in common (such as geography or ideology), learning via intermediaries such as ‘entrepreneurs’, or limiting their searches for evidence of success.
  • driven by various forms of pressure, including encouragement by central (or supranational) governments, international norms or agreements, ‘spillover’ effects causing one system to respond to innovation by another, or demands by businesses to minimise the cost of doing business.

In that context, some of the literature focuses on warning against unsuccessful policy transfer caused by factors such as:

  • Failing to generate or use enough evidence on what made the initial policy successful
  • Failing to adapt that policy to local circumstances
  • Failing to back policy change with sufficient resources

However, other studies highlight some major qualifications:

  • If the process is about using ideas about one system to inform another, our attention may shift from ‘transfer’ to ‘translation’ or ‘transformation’, and the idea of ‘successful transfer’ makes less sense
  • Transfer success is not the same as implementation success, which depends on a wider range of factors
  • Nor is it the same as ‘policy success’, which can be assessed by a mix of questions to reflect political reality: did it make the government more re-electable, was the process of change relatively manageable, and did it produce intended outcomes?

The use of evidence to spread policy innovation requires a combination of profound political and governance choices

When encouraging policy diffusion within a political system, choices about: (a) what counts as ‘good’ evidence of policy success have a major connection to (b) what counts as good governance.

For example, consider these ideal-types or models in table 1:

Table 1 3 ideal types of EBBP

In one scenario, we begin by relying primarily on RCT evidence (multiple international trials) and import a relatively fixed model, to ensure ‘fidelity’ to a proven intervention and allow us to measure its effect in a new context. This choice of good evidence limits the ability of subnational policymakers to adapt policy to local contexts.

In another scenario, we begin by relying primary on governance principles, such as to respect local discretion as well as incorporate practitioner and user experience as important knowledge claims. The choice of governance model relates closely to a less narrow sense of what counts as good evidence, but also a more limited ability to evaluate policy success scientifically.

In other words, the political choice to privilege some forms of evidence is difficult to separate from another political choice to privilege the role of one form of government.

Telling a policy transfer story: 11 questions to encourage successful evidence based policy transfer  

In that context, these steps to evidence-informed policy transfer serve more to encourage reflection than provide a blueprint for action. I accept that 11 is less catchy than 10.

  1. What problem did policymakers say they were trying to solve, and why?
  2. What solution(s) did they produce?
  3. Why?

Points 1-3 represent the classic and necessary questions from policy studies: (1) ‘what is policy?’ (2)  ‘how much did policy change?’ and (3) why? Until we have a good answer, we do not know how to draw comparable lessons. Learning from another government’s policy choices is no substitute for learning from more meaningful policy change.

4. Was the project introduced in a country or region which is sufficiently comparable? Comparability can relate to the size and type of country, the nature of the problem, the aims of the borrowing/ lending government and their measures of success.

5. Was it introduced nationwide, or in a region which is sufficiently representative of the national experience (it is not an outlier)?

6. How do we account for the role of scale, and the different cultures and expectations in each policy field?

Points 4-6 inform initial background discussions of case study reports. We need to focus on comparability when describing the context in which the original policy developed. It is not enough to state that two political systems are different. We need to identify the relevance and implications of the differences, from another government’s definition of the problem to the logistics of their task.

7. Has the project been evaluated independently, subject to peer review and/ or using measures deemed acceptable to the government?

8. Has the evaluation been of a sufficient period in proportion to the expected outcomes?

9. Are we confident that this project has been evaluated the most favourably – i.e. that our search for relevant lessons has been systematic, based on recognisable criteria (rather than reputations)?

10. Are we identifying ‘Good practice’ based on positive experience, ‘Promising approaches’ based on positive but unsystematic findings, ‘Research–based’ or based on ‘sound theory informed by a growing body of empirical research’, or ‘Evidence–based’, when ‘the programme or practice has been rigorously evaluated and has consistently been shown to work’?

Points 7-10 raise issues about the relationships between (a) what evidence we should use to evaluate success or potential, and (b) how long we should wait to declare success.

11. What will be the relationship between evidence and governance?

Should we identify the same basic model and transfer it uniformly, tell a qualitative story about the model and invite people to adapt it, or focus pragmatically on an eclectic range of evidential sources and focus on the training of the actors who will implement policy?

In conclusion

Information technology has allowed us to gather a huge amount of policy-relevant information across the globe. However, it has not solved the limitations we face in defining policy problems clearly, gathering evidence on policy solutions systematically, and generating international lessons that we can use to inform domestic policy processes.

This rise in available evidence is not a substitute for policy analysis and political choice. These choices range from how to adjudicate between competing policy preference, to how to define good evidence and good government. A lack of attention to these wider questions helps explain why – at least from some perspectives – policy transfer seems to fail.

Paul Cairney Auckland Policy Transfer 12.10.18

 

 

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The Politics of Evidence-Based Policymaking: ANZSOG talks

This post introduces a series of related talks on ‘the politics of evidence-based policymaking’ (EBPM) that I’m giving as part of larger series of talks during this ANZOG-funded/organised trip.

The EBPM talks begin with a discussion of the same three points: what counts as evidence, why we must ignore most of it (and how), and the policy process in which policymakers use some of it. However, the framing of these points, and the ways in which we discuss the implications, varies markedly by audience. So, in this post, I provide a short discussion of the three points, then show how the audience matters (referring to the city as a shorthand for each talk).

The overall take-home points are highly practical, in the same way that critical thinking has many practical applications (in other words, I’m not offering a map, toolbox, or blueprint):

  • If you begin with (a) the question ‘why don’t policymakers use my evidence?’ I like to think you will end with (b) the question ‘why did I ever think they would?’.
  • If you begin by taking the latter as (a) a criticism of politics and policymakers, I hope you will end by taking it as (b) a statement of the inevitability of the trade-offs that must accompany political choice.
  • We may address these issues by improving the supply and use of evidence. However, it is more important to maintain the legitimacy of the politicians and political systems in which policymakers choose to ignore evidence. Technocracy is no substitute for democracy.

3 ways to describe the use of evidence in policymaking

  1. Discussions of the use of evidence in policy often begin as a valence issue: who wouldn’t want to use good evidence when making policy?

However, it only remains a valence issue when we refuse to define evidence and justify what counts as good evidence. After that, you soon see the political choices emerge. A reference to evidence is often a shorthand for scientific research evidence, and good often refers to specific research methods (such as randomised control trials). Or, you find people arguing very strongly in the almost-opposite direction, criticising this shorthand as exclusionary and questioning the ability of scientists to justify claims to superior knowledge. Somewhere in the middle, we find that a focus on evidence is a good way to think about the many forms of information or knowledge on which we might make decisions, including: a wider range of research methods and analyses, knowledge from experience, and data relating to the local context with which policy would interact.

So, what begins as a valence issue becomes a gateway to many discussions about how to understand profound political choices regarding: how we make knowledge claims, how to ‘co-produce’ knowledge via dialogue among many groups, and the relationship between choices about evidence and governance.

  1. It is impossible to pay attention to all policy relevant evidence.

There is far more information about the world than we are able to process. A focus on evidence gaps often gives way to the recognition that we need to find effective ways to ignore most evidence.

There are many ways to describe how individuals combine cognition and emotion to limit their attention enough to make choices, and policy studies (to all intents and purposes) describe equivalent processes – described, for example, as ‘institutions’ or rules – in organisations and systems.

One shortcut between information and choice is to set aims and priorities; to focus evidence gathering on a small number of problems or one way to define a problem, and identify the most reliable or trustworthy sources of evidence (often via evidence ‘synthesis’). Another is to make decisions quickly by relying on emotion, gut instinct, habit, and existing knowledge or familiarity with evidence.

Either way, agenda setting and problem definition are political processes that address uncertainty and ambiguity. We gather evidence to reduce uncertainty, but first we must reduce ambiguity by exercising power to define the problem we seek to solve.

  1. It is impossible to control the policy process in which people use evidence.

Policy textbooks (well, my textbook at least!) provide a contrast between:

  • The model of a ‘policy cycle’ that sums up straightforward policymaking, through a series of stages, over which policymakers have clear control. At each stage, you know where evidence fits in: to help define the problem, generate solutions, and evaluate the results to set the agenda for the next cycle.
  • A more complex ‘policy process’, or policymaking environment, of which policymakers have limited knowledge and even less control. In this environment, it is difficult to know with whom engage, the rules of engagement, or the likely impact of evidence.

Overall, policy theories have much to offer people with an interest in evidence-use in policy, but primarily as a way to (a) manage expectations, to (b) produce more realistic strategies and less dispiriting conclusions. It is useful to frame our aim as to analyse the role of evidence within a policy process that (a) we don’t quite understand, rather than (b) we would like to exist.

The events themselves

Below, you will find a short discussion of the variations of audience and topic. I’ll update and reflect on this discussion (in a revised version of this post) after taking part in the events.

Social science and policy studies: knowledge claims, bounded rationality, and policy theory

For Auckland and Wellington A, I’m aiming for an audience containing a high proportion of people with a background in social science and policy studies. I describe the discussion as ‘meta’ because I am talking about how I talk about EBPM to other audiences, then inviting discussion on key parts of that talk, such as how to conceptualise the policy process and present conceptual insights to people who have no intention of deep dives into policy theory.

I often use the phrase ‘I’ve read it, so you don’t have to’ partly as a joke, but also to stress the importance of disciplinary synthesis when we engage in interdisciplinary (and inter-professional) discussion. If so, it is important to discuss how to produce such ‘synthetic’ accounts.

I tend to describe key components of a policymaking environment quickly: many policy makers and influencers spread across many levels and types of government, institutions, networks, socioeconomic factors and events, and ideas. However, each of these terms represents a shorthand to describe a large and diverse literature. For example, I can describe an ‘institution’ in a few sentences, but the study of institutions contains a variety of approaches.

Background post: I know my audience, but does my other audience know I know my audience?

Academic-practitioner discussions: improving the use of research evidence in policy

For Wellington B and Melbourne, the audience is an academic-practitioner mix. We discuss ways in which we can encourage the greater use of research evidence in policy, perhaps via closer collaboration between suppliers and users.

Discussions with scientists: why do policymakers ignore my evidence?

Sydney UNSW focuses more on researchers in scientific fields (often not in social science).  I frame the question in a way that often seems central to scientific researcher interest: why do policymakers seem to ignore my evidence, and what can I do about it?

Then, I tend to push back on the idea that the fault lies with politics and policymakers, to encourage researchers to think more about the policy process and how to engage effectively in it. If I’m trying to be annoying, I’ll suggest to a scientific audience that they see themselves as ‘rational’ and politicians as ‘irrational’. However, the more substantive discussion involves comparing (a) ‘how to make an impact’ advice drawn from the personal accounts of experienced individuals, giving advice to individuals, and (b) the sort of advice you might draw from policy theories which focus more on systems.

Background post: What can you do when policymakers ignore your evidence?

Early career researchers: the need to build ‘impact’ into career development

Canberra UNSW is more focused on early career researchers. I think this is the most difficult talk because I don’t rely on the same joke about my role: to turn up at the end of research projects to explain why they failed to have a non-academic impact.  Instead, my aim is to encourage intelligent discussion about situating the ‘how to’ advice for individual researchers into a wider discussion of policymaking systems.

Similarly, Brisbane A and B are about how to engage with practitioners, and communicate well to non-academic audiences, when most of your work and training is about something else entirely (such as learning about research methods and how to engage with the technical language of research).

Background posts:

What can you do when policymakers ignore your evidence? Tips from the ‘how to’ literature from the science community

What can you do when policymakers ignore your evidence? Encourage ‘knowledge management for policy’

See also:

  1. A similar talk at LSHTM (powerpoint and audio)

2. European Health Forum Gastein 2018 ‘Policy in Evidence’ (from 6 minutes)

https://webcasting.streamdis.eu/Mediasite/Play/8143157d976146b4afd297897c68be5e1d?catalog=62e4886848394f339ff678a494afd77f21&playFrom=126439&autoStart=true

 

See also:

Evidence-based policymaking and the new policy sciences

 

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Talks and blogs: ANZSOG and beyond

In 2018, I took a trip to New Zealand and Australia as a guest of ANZSOG. Here is a list of dates and titles for each talk (followed by some talks in Europe from 2018). There is usually a link in the name of the city to the advert for the talk. There is also a link in each title to a blog post on the talk. Some of the talks were recorded and I will add them when I get them. In the meantime, there is also a selection of tweets at the end to prove that I’m not making up the trip.

  1. Auckland 11 October University of Auckland (mostly academic audience) Why don’t policymakers listen to my evidence (powerpoint) (recorded lecture)
  2. Auckland 12 October Auckland Art Gallery (NZ public managers from Auckland council and State sector agencies)  Teaching evidence-based policy to fly: transferring sound policies across the world (not recorded)
  3. Auckland 12 October Working with complexity – evidence based practice and practice based evidence (including Auckland Co-design Lab and Southern Initiative, roundtable discussion of this kind of thing)
  4. Wellington October 15 The politics of evidence-based policy: the expectations of academics and policymakers and ways to meet in the middle (Policy Project, Department of the Prime Minister and Cabinet, discussion based on this kind of old post, new post, and powerpoint presentation, followed by their summary)
  5. Wellington 15 October (200 NZ civil servants from Wellington-based departments and agencies) Prevention is better than cure: so why aren’t we doing more of it? (ppt)
  6. Wellington 16 October Victoria University (academic audience) The politics of evidence-based policy
  7. Wellington 17 October Victoria University (academic audience) Blogging and reaching out (see discussion of previous event and Q. Should PhD students blog? A. Yes)
  8. Melbourne 18 October (Department of Premier and Cabinet, Victoria State Government) The politics of evidence-based policy making (DPC)
  9. Sydney UNSW 19 October Why don’t policymakers listen to your evidence? (ppt presentation then roundtable on impact – videos below)
  10. Canberra (ANU) 22 October Taking lessons from policy theory into practice (lecture and discussion). Powerpoint here. Audio (skip to 2m30) (or right click download or dropbox link
  11. Canberra (ANU) 22 October podcast ‘Why prevention policies fail
  12. Canberra (UNSW) 23 October Why might policymakers listen to your evidence? (PhD workshop, discussing elements of a ppt I used for the SGSSS and this powerpoint presentation that I’ve used with UK and Scottish government audiences and in Wellington)
  13. Brisbane 24 October University of Queensland Theory and Practice: How to Communicate Policy Research beyond the Academy Blog PPT MP3
  14. Brisbane 25 October University of Queensland Evidence-based policymaking and the new policy sciences (see ppt & MP3 and article with Chris Weible)

UQ isn’t really a big tweety place, so here is a picture of a lovely tree there:

See also:

London

Austria

European Health Forum Gastein 2018 ‘Policy in Evidence’ (from 6 minutes)

Institute of Development Studies, 17 January 2019

https://twitter.com/Bloggs74/status/1085874777158500352

 

 

 

 

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